Citations (42)
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Andrey A. Toropov, Alla P. Toropova & Emilio Benfenati. (2020) ‘Ideal correlations’ for the predictive toxicity to Tetrahymena pyriformis. Toxicology Mechanisms and Methods 30:8, pages 605-610.
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P. Kumar & A. Kumar. (2020) In silico enhancement of azo dye adsorption affinity for cellulose fibre through mechanistic interpretation under guidance of QSPR models using Monte Carlo method with index of ideality correlation. SAR and QSAR in Environmental Research 31:9, pages 697-715.
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S. Bhargava, N. Adhikari, S. A. Amin, K. Das, S. Gayen & T. Jha. (2017) Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization. SAR and QSAR in Environmental Research 28:12, pages 973-990.
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A. Kumar & S. Chauhan. (2017) Monte Carlo method based QSAR modelling of natural lipase inhibitors using hybrid optimal descriptors. SAR and QSAR in Environmental Research 28:3, pages 179-197.
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V. Prachayasittikul, A. Worachartcheewan, A. P. Toropova, A. A. Toropov, N. Schaduangrat, V. Prachayasittikul & C. Nantasenamat. (2017) Large-scale classification of P-glycoprotein inhibitors using SMILES-based descriptors. SAR and QSAR in Environmental Research 28:1, pages 1-16.
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M. Stec, T. Spietz, L. Więcław-Solny, A. Tatarczuk & A. Krótki. (2015) Predicting normal densities of amines using quantitative structure-property relationship (QSPR) . SAR and QSAR in Environmental Research 26:11, pages 893-904.
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S. Begum & P. Ganga Raju Achary. (2015) Simplified molecular input line entry system-based: QSAR modelling for MAP kinase-interacting protein kinase (MNK1). SAR and QSAR in Environmental Research 26:5, pages 343-361.
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A.P. Toropova, A.A. Toropov & E. Benfenati. (2015) A quasi-QSPR modelling for the photocatalytic decolourization rate constants and cellular viability (CV%) of nanoparticles by CORAL. SAR and QSAR in Environmental Research 26:1, pages 29-40.
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Articles from other publishers (34)
Bhawna, Sunil Kumar, Parvin Kumar & Ashwani Kumar. (2024) Correlation intensity index-index of ideality of correlation: A hyphenated target function for furtherance of MAO-B inhibitory activity assessment. Computational Biology and Chemistry 108, pages 107975.
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Alla P. Toropova, Andrey A. Toropov, Parvin Kumar, Ashwani Kumar & P. Ganga Raju Achary. (2023) Fragments of local symmetry in a sequence of amino acids: Does one can use for QSPR/QSAR of peptides?. Journal of Molecular Structure 1293, pages 136300.
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Nilima R. Das, Tripti Sharma, Nainee Goyal, Nagendra Singh, Andrey A. Toropov, Alla P. Toropova & P. Ganga Raju Achary. (2023) Isoprenylcysteine carboxyl methyltransferase inhibitors: QSAR, docking and molecular dynamics studies. Journal of Molecular Structure 1291, pages 135966.
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Andrey A. Toropov, Maria Raskova, Ivan RaskaJr.Jr. & Alla P. Toropova. 2023. QSPR/QSAR Analysis Using SMILES and Quasi-SMILES. QSPR/QSAR Analysis Using SMILES and Quasi-SMILES
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Nilima R. Das, Krishnendu Bera, Tripti Sharma, Alla P. Toropova, Andrey A. Toropov & P. Ganga Raju Achary. (2022) Computational approach for building QSAR models for inhibition of HIF-1A. Journal of the Indian Chemical Society 99:10, pages 100687.
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Sayandeep Deoghuria, Aastha Mahapatra, Nilima R. Das, P. Ganga Raju Achary & Tripti Sharma. (2022) QSAR Study, Molecular Docking, and Pharmacokinetic Analysis of Substituted Dihydropyrimidinone as ErbB2 Inhibitors. International Journal of Quantitative Structure-Property Relationships 7:1, pages 1-17.
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N. R. Das & P. G. R. Achary. (2021) Prediction of pEC50(M) and molecular docking study for the selective inhibition of arachidonate 5-lipoxygenase. The Ukrainian Biochemical Journal 93:6, pages 101-118.
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Nilima R. Das & P. Ganga Raju Achary. (2021) Machine Learning based Approach in Building QSAR Models for the Study of Asparagine Endopeptidase. Machine Learning based Approach in Building QSAR Models for the Study of Asparagine Endopeptidase.
Alla P. Toropova, Andrey A. Toropov & Emilio Benfenati. (2021) The self-organizing vector of atom-pairs proportions: use to develop models for melting points. Structural Chemistry 32:3, pages 967-971.
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Patnala Ganga Raju Achary, Alla P. Toropova & Andrey A. Toropov. (2020) Prediction of the self‐accelerating decomposition temperature of organic peroxides. Process Safety Progress 40:2.
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Nilima Rani Das, Sneha Prabha Mishra & P. Ganga Raju Achary. (2021) Evaluation of molecular structure based descriptors for the prediction of pEC50(M) for the selective adenosine A2A Receptor. Journal of Molecular Structure 1232, pages 130080.
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Sharda Sundaram Sanjay & Ashutosh Kumar ShuklaSharda Sundaram Sanjay & Ashutosh Kumar Shukla. 2021. Potential Therapeutic Applications of Nano-antioxidants. Potential Therapeutic Applications of Nano-antioxidants
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Nilima Rani Das & P. Ganga Raju Achary. 2021. Advances in Intelligent Computing and Communication. Advances in Intelligent Computing and Communication
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Andrey A. Toropov & Alla P. Toropova. (2019) QSAR as a random event: criteria of predictive potential for a chance model. Structural Chemistry 30:5, pages 1677-1683.
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Andrey A. Toropov, Ivan RaškaJrJr, Alla P. Toropova, Maria Raškova, Aleksandar M. Veselinović & Jovana B. Veselinović. (2019) The study of the index of ideality of correlation as a new criterion of predictive potential of QSPR/QSAR-models. Science of The Total Environment 659, pages 1387-1394.
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Andrey Andreevich Toropov, Alla Petrovna Toropova & Emilio Benfenati. (2019) The Index of Ideality of Correlation: QSAR Model of Acute Toxicity for Zebrafish (Danio rerio) Embryo. International Journal of Environmental Research 13:2, pages 387-394.
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Yasunari Matsuzaka & Yoshihiro Uesawa. (2019) Optimization of a Deep-Learning Method Based on the Classification of Images Generated by Parameterized Deep Snap a Novel Molecular-Image-Input Technique for Quantitative Structure–Activity Relationship (QSAR) Analysis. Frontiers in Bioengineering and Biotechnology 7.
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Ashwani Kumar & Shilpi Chauhan. (2018) Use of Simplified Molecular Input Line Entry System and molecular graph based descriptors in prediction and design of pancreatic lipase inhibitors. Future Medicinal Chemistry 10:13, pages 1603-1622.
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Karel Nesměrák, Andrey A. Toropov, Alla P. Toropova, Tugba Ertan-Bolelli & Ilkay Yildiz. (2017) QSAR of antimycobacterial activity of benzoxazoles by optimal SMILES-based descriptors. Medicinal Chemistry Research 26:12, pages 3203-3208.
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Andrey A. Toropov & Alla P. Toropova. (2017) The index of ideality of correlation: A criterion of predictive potential of QSPR/QSAR models?. Mutation Research/Genetic Toxicology and Environmental Mutagenesis 819, pages 31-37.
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Alla P. Toropova & Andrey A. Toropov. (2017) The index of ideality of correlation: A criterion of predictability of QSAR models for skin permeability?. Science of The Total Environment 586, pages 466-472.
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Alla P. Toropova & Andrey A. Toropov. (2017) CORAL: Binary classifications (active/inactive) for drug-induced liver injury. Toxicology Letters 268, pages 51-57.
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Alla P. Toropova, P. Ganga Raju Achary & Andrey A. Toropov. 2017. Materials Science and Engineering. Materials Science and Engineering
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Alla P. Toropova, P. Ganga Raju Achary & Andrey A. Toropov. 2017. Pharmaceutical Sciences. Pharmaceutical Sciences
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Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Orazio Nicolotti, Angelo Carotti, Karel Nesmerak, Aleksandar M. Veselinović, Jovana B. Veselinović, Pablo R. Duchowicz, Daniel Bacelo, Eduardo A. Castro, Bakhtiyor F. Rasulev, Danuta Leszczynska & Jerzy Leszczynski. 2017. Pharmaceutical Sciences. Pharmaceutical Sciences
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Alla P. Toropova, Andrey A. Toropov, Aleksandar M. Veselinović, Jovana B. Veselinović, Danuta Leszczynska & Jerzy Leszczynski. (2016)
Monte Carlo–based quantitative structure–activity relationship models for toxicity of organic chemicals to
Daphnia magna
. Environmental Toxicology and Chemistry 35:11, pages 2691-2697.
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Andrey A. Toropov, P. Ganga Raju Achary & Alla P. Toropova. (2016) Quasi-SMILES and nano-QFPR: The predictive model for zeta potentials of metal oxide nanoparticles. Chemical Physics Letters 660, pages 107-110.
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Alla P. Toropova & Andrey A. Toropov. (2016) Assessment of nano-QSPR models of organic contaminant absorption by carbon nanotubes for ecological impact studies. Materials Discovery 4, pages 22-28.
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Andrey A. Toropov, Alla P. Toropova, Karel Nesmerak, Aleksandar M. Veselinovi?Jovana B. Veselinovi?Danuta Leszczynska & Jerzy Leszczynski. 2016. Practical Aspects of Computational Chemistry IV. Practical Aspects of Computational Chemistry IV
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Andrey A. Toropov & Alla P. Toropova. (2015) Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes. Chemosphere 124, pages 40-46.
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Andrey A. Toropov, Alla P. Toropova, Emilio Benfenati, Orazio Nicolotti, Angelo Carotti, Karel Nesmerak, Aleksandar M. Veselinović, Jovana B. Veselinović, Pablo R. Duchowicz, Daniel Bacelo, Eduardo A. Castro, Bakhtiyor F. Rasulev, Danuta Leszczynska & Jerzy Leszczynski. 2015. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment. Quantitative Structure-Activity Relationships in Drug Design, Predictive Toxicology, and Risk Assessment
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Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Rafi Korenstein, Danuta Leszczynska & Jerzy Leszczynski. (2014) Optimal nano-descriptors as translators of eclectic data into prediction of the cell membrane damage by means of nano metal-oxides. Environmental Science and Pollution Research 22:1, pages 745-757.
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Apilak Worachartcheewan, Prasit Mandi, Virapong Prachayasittikul, Alla P. Toropova, Andrey A. Toropov & Chanin Nantasenamat. (2014) Large-scale QSAR study of aromatase inhibitors using SMILES-based descriptors. Chemometrics and Intelligent Laboratory Systems 138, pages 120-126.
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Alla P. Toropova, Andrey A. Toropov, Emilio Benfenati, Tomasz Puzyn, Danuta Leszczynska & Jerzy Leszczynski. (2014) Optimal descriptor as a translator of eclectic information into the prediction of membrane damage: The case of a group of ZnO and TiO2 nanoparticles. Ecotoxicology and Environmental Safety 108, pages 203-209.
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